Development of a Single-Moment Cloud Microphysics Scheme with Prognostic Hail for the Weather Research and Forecasting (WRF) Model

2018 ◽  
Vol 55 (2) ◽  
pp. 233-245 ◽  
Author(s):  
Soo Ya Bae ◽  
Song-You Hong ◽  
Wei-Kuo Tao
Keyword(s):  
Wrf Model ◽  
Cloud Microphysics ◽  
Weather Research And Forecasting ◽  
Microphysics Scheme ◽  
Single Moment ◽  
Weather Research

scholarly journals Intel Xeon Phi accelerated Weather Research and Forecasting (WRF) Goddard microphysics scheme

2014 ◽  
Vol 7 (6) ◽  
pp. 8941-8973 ◽  
Author(s):  
J. Mielikainen ◽  
B. Huang ◽  
A. H.-L. Huang
Keyword(s):  
Wrf Model ◽  
Cloud Microphysics ◽  
Optimization Techniques ◽  
Weather Research And Forecasting ◽  
Xeon Phi ◽  
Microphysics Scheme ◽  
Improved Performance ◽  
Intel Mic ◽  
Intel Xeon ◽  
Weather Research

Abstract. The Weather Research and Forecasting (WRF) model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and so on. The WRF contains several physics components. The most time consuming one is the microphysics. One microphysics scheme is the Goddard cloud microphysics scheme. It is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the Goddard scheme code. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU does. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is one familiar to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discussed in this paper. The results show that the optimizations improved performance of Goddard microphysics scheme on Xeon Phi 7120P by a factor of 4.7×. In addition, the optimizations reduced the Goddard microphysics scheme's share of the total WRF processing time from 20.0 to 7.5%. Furthermore, the same optimizations improved performance on Intel Xeon E5-2670 by a factor of 2.8× compared to the original code.

scholarly journals Evaluation of Weather Research and Forecasting (WRF) Microphysics single moment class-3 and class-6 in Precipitation Forecast

2018 ◽  
Vol 150 ◽  
pp. 03007 ◽  
Author(s):  
Syeda Maria Zaidi ◽  
Jacqueline Isabella Anak Gisen
Keyword(s):  
Model Performance ◽  
Wrf Model ◽  
Precipitation Forecast ◽  
Weather Research And Forecasting ◽  
Microphysics Scheme ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Single Moment ◽  
Minimum Medium ◽  
Weather Research

In this study, the performance of two different Microphysics Scheme options in Weather Research and Forecasting (WRF) model were evaluated for the estimating the precipitation forecast. The schemes WRF single moment class-3 (WSM-3) and single moment class-6 (WSM-6) were employed to produce the minimum, medium and maximum precipitation for the selected events over the Kuantan River Basin (KRB). The obtained simulated results were compared with the observed data from eight different rainfall gauging stations. The results comparison indicate that WRF model provides better forecasting at some rainfall stations for minimum and medium rainfall events but did not produce good result during maximum rainfall overall. The WSM-6 scheme is found to produce better result compared to WSM-3. The study also found that to acquire accurate precipitation results, it is also required to test some other physics scheme parameterization to enhance the model performance.

scholarly journals High resolution simulations of a tornadic storm affecting Sydney

2021 ◽  
Vol 62 ◽  
Author(s):  
Joshua Hartigan ◽  
Shev MacNamara ◽  
Lance Leslie ◽  
Milton Speer
Keyword(s):  
Wrf Model ◽  
Cloud Microphysics ◽  
Squall Line ◽  
Weather Research And Forecasting ◽  
Cold Pool ◽  
Microphysics Scheme ◽  
Severe Storms ◽  
Severe Thunderstorms ◽  
Sydney Australia ◽  
Weather Research

On 16 December 2015 a severe thunderstorm and associated tornado affected Sydney causing widespread damage and insured losses of $206 million. Severe impacts occurred in Kurnell, requiring repairs to Sydney's desalination plant which supplies up to 15% of Sydney water during drought, with repairs only completed at the end of 2018. Climatologically, this storm was unusual as it occurred during the morning and had developed over the ocean, rather than developing inland during the afternoon as is the case for many severe storms impacting the Sydney region. Simulations of the Kurnell storm were conducted using the Weather Research and Forecasting (WRF) model on a double nested domain using the Morrison microphysics scheme and the NSSL 2-moment 4-ice microphysics scheme. Both simulations produced severe storms that followed paths similar to the observed storm. However, the storm produced under the Morrison scheme did not have the same morphology as the observed storm. Meanwhile, the storm simulated with the NSSL scheme displayed cyclical low- and mid-level mesocyclone development, which was observed in the Kurnell storm, highlighting that the atmosphere supported the development of severe rotating thunderstorms with the potential for tornadogenesis. The NSSL storm also produced severe hail and surface winds, similar to observations. The ability of WRF to simulate general convective characteristics and a storm similar to that observed displays the applicability of this model to study the causes of severe high-impact Australian thunderstorms. References J. T. Allen and E. R. Allen. A review of severe thunderstorms in Australia. Atmos. Res., 178:347–366, 2016. doi:10.1016/j.atmosres.2016.03.011. Bureau of Meteorology. Severe Storms Archive, 2020. URL http://www.bom.gov.au/australia/stormarchive/. D. T. Dawson II, M. Xue, J. A. Milbrandt, and M. K. Yau. Comparison of evaporation and cold pool development between single-moment and multimoment bulk microphysics schemes in idealized simulations of tornadic thunderstorms. Month. Wea. Rev., 138:1152–1171, 2010. doi:10.1175/2009MWR2956.1. H. Hersbach, B. Bell, P. Berrisford, S. Hirahara, A. Horanyi, J. Munoz-Sabater, J. Nicolas, C. Peubey, R. Radu, D. Schepers, et al. The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146:1999–2049, 2020. doi:10.1002/qj.3803. Insurance Council of Australia. Victorian bushfire losses push summer catastrophe bill past $550m, 2016. E. R. Mansell, C. L. Ziegler, and E. C. Bruning. Simulated electrification of a small thunderstorm with two-moment bulk microphysics. J. Atmos. Sci., 67:171–194, 2010. doi:10.1175/2009JAS2965.1. R. C. Miller. Notes on analysis and severe-storm forecasting procedures of the Air Force Global Weather Central, volume 200. Air Weather Service, 1972. URL https://apps.dtic.mil/sti/citations/AD0744042. H. Morrison, J. A. Curry, and V. I. Khvorostyanov. A new double-moment microphysics parameterization for application in cloud and climate models. Part I: Description. J. Atmos. Sci., 62:1665–1677, 2005. doi:10.1175/JAS3446.1. H. Morrison, G. Thompson, and V. Tatarskii. Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Month. Wea. Rev., 137:991–1007, 2009. doi:10.1175/2008MWR2556.1. J. G. Powers, J. B. Klemp, W. C. Skamarock, C. A. Davis, J. Dudhia, D. O. Gill, J. L. Coen, D. J. Gochis, R. Ahmadov, S. E. Peckham, et al. The Weather Research and Forecasting Model: Overview, system efforts, and future directions. Bull. Am. Meteor. Soc., 98:1717–1737, 2017. doi:10.1175/BAMS-D-15-00308.1. H. Richter, A. Protat, J. Taylor, and J. Soderholm. Doppler radar and storm environment observations of a maritime tornadic supercell in Sydney, Australia. In Preprints, 28th Conf. on Severe Local Storms, Portland OR, Amer. Meteor. Soc. P, 2016. W. C. Skamarock, J. B. Klemp, J. Dudhia, D. O. Gill, Z. Liu, J. Berner, W. Wang, J. G. Powers, M. G. Duda, D. Barker, and X.-Y. Huang. A description of the advanced research WRF Model version 4. Technical report, 2019. Storm Prediction Center. The Enhanced Fujita Scale (EF Scale), 2014. URL https://www.spc.noaa.gov/efscale/. R. A. Warren, H. A. Ramsay, S. T. Siems, M. J. Manton, J. R. Peter, A. Protat, and A. Pillalamarri. Radar-based climatology of damaging hailstorms in Brisbane and Sydney, Australia. Quart. J. Roy. Meteor. Soc., 146:505–530, 2020. doi:10.1002/qj.3693.

scholarly journals Simulation of Severe Thunderstorms in Conjugation of Westerly and Easterly on 31 March 2019 in Bangladesh

2022 ◽  
Vol 12 (3) ◽  
pp. 29-43
Author(s):  
Samarendra Karmakar ◽  
Mohan Kumar Das ◽  
Md Quamrul Hassam ◽  
Md Abdul Mannan
Keyword(s):  
South Asian ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Microphysics Scheme ◽  
Severe Thunderstorms ◽  
Synoptic Conditions ◽  
Pbl Scheme ◽  
Single Moment

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

scholarly journals Influence of Bulk Microphysics Schemes upon Weather Research and Forecasting (WRF) Version 3.6.1 Nor'easter Simulations

2016 ◽  
Author(s):  
Stephen D. Nicholls ◽  
Steven G. Decker ◽  
Wei-Kuo Tao ◽  
Stephen E. Lang ◽  
Jainn J. Shi ◽  
...  
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Large Variability ◽  
Mixing Ratios ◽  
Simulated Precipitation ◽  
Single Moment ◽  
Double Moment ◽  
Order Of Magnitude ◽  
The Impact ◽  
Weather Research

Abstract. This study evaluated the impact of five, single- or double- moment bulk microphysics schemes (BMPS) on Weather Research and Forecasting (WRF) model (version 3.6.1) winter storm simulations. Model simulations were integrated for 180 hours, starting 72 hours prior to the first measurable precipitation in the highly populated Mid-Atlantic U.S. Simulated precipitation fields were well-matched to precipitation products. However, total accumulations tended to be over biased (1.10–2.10) and exhibited low-to-moderate threat scores (0.27–0.59). Non-frozen hydrometeor species from single-moment BMPS produced similar mixing ratio profiles and maximum saturation levels due to a common parameterization heritage. Greater variability occurred with frozen microphysical species due to varying assumptions among BMPSs regarding ice supersaturation amounts, the dry collection of snow by graupel, various ice collection efficiencies, snow and graupel density and size mappings/intercept parameters, and hydrometeor terminal velocities. The addition of double-moment rain and cloud water resulted in minimal change to species spatial extent or maximum saturation level, however rain mixing ratios tended higher. Although hydrometeor differences varied by up to an order of magnitude among the BMPSs, similarly large variability was not upscaled to mesoscale and synoptic scales.

scholarly journals Extreme Rainfall Forecast with the WRF-ARW Model in the Central Andes of Peru

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 362 ◽  
Author(s):  
Aldo Moya-Álvarez ◽  
José Gálvez ◽  
Andrea Holguín ◽  
René Estevan ◽  
Shailendra Kumar ◽  
...  
Keyword(s):  
Extreme Event ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Central Andes ◽  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Microphysics Scheme ◽  
Vertical Movements ◽  
Synoptic Conditions ◽  
Weather Research

The ability of the WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to forecast extreme rainfall in the Central Andes of Peru is evaluated in this study, using observations from stations located in the Mantaro basin and GOES (Geostationary Operational Environmental Satellite) images. The evaluation analyzes the synoptic conditions averaged over 40 extreme event cases, and considers model simulations organized in 4 nested domains. We first establish that atypical events in the region are those with more than 27 mm of rainfall per day when averaging over all the stations. More than 50% of the selected cases occurred during January, February, and April, with the most extreme occurring during February. The average synoptic conditions show negative geopotential anomalies and positive humidity anomalies in 700 and 500 hPa. At 200 hPa, the subtropical upper ridge or “Bolivian high” was present, with its northern divergent flank over the Mantaro basin. Simulation results show that the Weather Research and Forecasting (WRF) model underestimates rainfall totals in approximately 50–60% of cases, mainly in the south of the basin and in the extreme west along the mountain range. The analysis of two case studies shows that the underestimation by the model is probably due to three reasons: inability to generate convection in the upstream Amazon during early morning hours, apparently related to processes of larger scales; limitations on describing mesoscale processes that lead to vertical movements capable of producing extreme rainfall; and limitations on the microphysics scheme to generate heavy rainfall.

scholarly journals Optimal Physics Parameterization Scheme Combination of the Weather Research and Forecasting Model for Seasonal Precipitation Simulation over Ghana

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Richard Yao Kuma Agyeman ◽  
Thompson Annor ◽  
Benjamin Lamptey ◽  
Emmanuel Quansah ◽  
Jacob Agyekum ◽  
...  
Keyword(s):  
Wrf Model ◽  
Mean Value ◽  
Weather Research And Forecasting ◽  
Seasonal Precipitation ◽  
Data Simulation ◽  
Microphysics Scheme ◽  
Precipitation Simulation ◽  
Outer Domain ◽  
Effects Of Drought ◽  
Weather Research

Seasonal predictions of precipitation, among others, are important to help mitigate the effects of drought and floods on agriculture, hydropower generation, disasters, and many more. This work seeks to obtain a suitable combination of physics schemes of the Weather Research and Forecasting (WRF) model for seasonal precipitation simulation over Ghana. Using the ERA-Interim reanalysis as forcing data, simulation experiments spanning eight months (from April to November) were performed for two different years: a dry year (2001) and a wet year (2008). A double nested approach was used with the outer domain at 50 km resolution covering West Africa and the inner domain covering Ghana at 10 km resolution. The results suggest that the WRF model generally overestimated the observed precipitation by a mean value between 3% and 64% for both years. Most of the scheme combinations overestimated (underestimated) precipitation over coastal (northern) zones of Ghana for both years but estimated precipitation reasonably well over forest and transitional zones. On the whole, the combination of WRF Single-Moment 6-Class Microphysics Scheme, Grell-Devenyi Ensemble Cumulus Scheme, and Asymmetric Convective Model Planetary Boundary Layer Scheme simulated the best temporal pattern and temporal variability with the least relative bias for both years and therefore is recommended for Ghana.

scholarly journals Sensitivity of Botswana Ex-Tropical Cyclone Dineo rainfall simulations to cloud microphysics scheme

2020 ◽  
Vol 3 ◽  
pp. 30 ◽  
Author(s):  
Charles Molongwane ◽  
Mary-Jane M. Bopape ◽  
Ann Fridlind ◽  
Tshiamo Motshegwa ◽  
Toshihisa Matsui ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Cloud Microphysics ◽  
Weather Research And Forecasting ◽  
Heavy Rainfall Event ◽  
Operational Forecasting ◽  
Outer Domain ◽  
Single Moment ◽  
Performance Computing ◽  
Weather Research

Background: Numerical weather and climate models rely on the use of microphysics schemes to simulate clouds and produce precipitation at convective scales. It is important that we understand how different microphysics schemes perform when simulating high impact weather to inform operational forecasting. Methods: Simulations a heavy rainfall event from 17-20 February 2017 over Botswana were made with the Weather Research and Forecasting (WRF) model using four different microphysics schemes. The schemes used were the Weather Research and Forecasting Single Moment 6-class scheme (WSM6); Weather Research and Forecasting Single Moment 5-class scheme (WSM5); Stony Brook University scheme (SBU-YLIN); and Thompson scheme. WSM5 is considered as the least sophisticated of the four schemes, while Thompson is the most sophisticated. Simulations were initialized and forced by the Global Forecast System (GFS), and configured with a grid spacing of 9km over an outer domain and 3km for a nested inner domain without the convection parameterization.  The simulations were produced using the University of Botswana and the Centre for High Performance Computing (CHPC) High Performance Computing (HPC) systems. Results: WSM5 and WSM6 simulations are mostly similar; the presence of graupel in WSM6 did not result in large differences in the rainfall simulations. SBU-YLIN simulated the least amount of rainfall, followed by Thompson. All the schemes captured the north-south rainfall gradient observed on 17 February, but with all simulations rainfall is simulated slightly south of where it was observed. All the schemes overestimated rainfall on 18 February over the central parts of Botswana, and underestimated rainfall on 19 February over most of Botswana. Conclusions: Simulations with different microphysics looked more similar to each other, than to observations. Future studies will test WRF configurations including a single nest over Botswana to determine the best configuration for operational forecasting by the Botswana Department of Meteorological Services.

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